1 citations · 1 across the 9 of their papers we have counts for
11 papers
EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation
Yiming Jiang, Chen Jin, Jin Chen +4
Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with missing robot states, limit thei…
EgoHumanoid-V2: Human-to-Humanoid Transfer of Coordinated Whole-Body Skills for Loco-Manipulation
Jin Chen, Yiming Jiang, Chongyang Xu +8
Human demonstrations capture diverse scenes and rich whole-body skills without requiring robot teleoperation. Prior work on egocentric transfer has emphasized scene generalization…
Stability-Driven Motion Generation for Object-Guided Human-Human Co-Manipulation
Jiahao Xu, Xiaohan Yuan, Xingchen Wu +3
Co-manipulation requires multiple humans to synchronize their motions with a shared object while ensuring reasonable interactions, maintaining natural poses, and preserving stable…
Contrastive Multi-Modal Hypergraph Reasoning for 3D Crowd Mesh Recovery
Minghao Sun, Chongyang Xu, Yitao Xie +2
Multi-person 3D reconstruction is pivotal for real-world interaction analysis, yet remains challenging due to severe occlusions and depth ambiguity. Current approaches typically re…
Ada3Drift: Adaptive Training-Time Drifting for One-Step 3D Visuomotor Robotic Manipulation
Chongyang Xu, Yixian Zou, Tianyu Yang +4
Diffusion-based visuomotor policies model complex action distributions through iterative denoising, but repeated inference adds latency to robotic control. One-step generators redu…
Action-Geometry Prediction with 3D Geometric Prior for Bimanual Manipulation
Chongyang Xu, Haipeng Li, Shen Cheng +4
Bimanual manipulation requires policies that can reason about 3D geometry, anticipate how it evolves under action, and generate smooth, coordinated motions. However, existing metho…
HeRO: Hierarchical 3D Semantic Representation for Pose-aware Object Manipulation
Chongyang Xu, Shen Cheng, Haipeng Li +3
Imitation learning for robotic manipulation has progressed from 2D image policies to 3D representations that explicitly encode geometry. Yet purely geometric policies often lack ex…
Reconstructing Close Human Interaction with Appearance and Proxemics Reasoning
Buzhen Huang, Chen Li, Chongyang Xu +4
Due to visual ambiguities and inter-person occlusions, existing human pose estimation methods cannot recover plausible close interactions from in-the-wild videos. Even state-of-the…
Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop
Tianxing Chen, Kaixuan Wang, Zhaohui Yang +96
Embodied Artificial Intelligence (Embodied AI) is an emerging frontier in robotics, driven by the need for autonomous systems that can perceive, reason, and act in complex physical…
Adapting Human Mesh Recovery with Vision-Language Feedback
Chongyang Xu, Buzhen Huang, Chengfang Zhang +2
Human mesh recovery can be approached using either regression-based or optimization-based methods. Regression models achieve high pose accuracy but struggle with model-to-image ali…
Closely Interactive Human Reconstruction with Proxemics and Physics-Guided Adaption
Buzhen Huang, Chen Li, Chongyang Xu +3
Existing multi-person human reconstruction approaches mainly focus on recovering accurate poses or avoiding penetration, but overlook the modeling of close interactions. In this wo…